• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2003년도 춘계학술대회 논문집
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• pp.327-339
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• 2003

In this paper, a self-organizing fuzzy controller(SOFC) for the industrial robot manipulator with a actuator located at the base is studied A fuzzy login composed of linguistic conditional statements is employed by defining the relations of input-output variable of the controller, In the synthesis of a FLC, one of the most difficult problems is the determination of linguistic control rules from the human operators. To overcome this difficult SOFC is proposed for a hierarchical control structure consisting of basic level and high level that modify control rules. The proposed SOFC scheme is simple in structure, fast in computations and suitable for implementation of real-time control. Performance of the SOFC is illustrated by simulation and experimental results for robot with low joints.

• 산업경영시스템학회지
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• 제23권61호
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• pp.127-135
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• 2000

This paper provides a new method of initializing neurons used in self-organizing neural networks and sequencing input nodes for applying to Euclidean traveling salesman problem. We use a general property that in any optimal solution for Euclidean traveling salesman problem, vertices located on the convex hull are visited in the order in which they appear on the convex hull boundary. We composite input nodes as number of convex hulls and initialize neurons as shape of the external convex hull. And then adapt input nodes as the convex hull unit and all convex hulls are adapted as same pattern, clockwise or counterclockwise. As a result of our experiments, we obtain l∼3 % improved solutions and these solutions can be used for initial solutions of any global search algorithms.

• 산업경영시스템학회지
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• 제23권61호
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• pp.137-146
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• 2000

One of the problems faced in implementing cellular manufacturing systems is machine-part group formation. This paper proposes machine-part grouping algorithms based on Self-Organizing Map(SOM) neural networks and K-Means algorithm in cellular manufacturing systems. Although the SOM spreads out input vectors to output vectors in the order of similarity, it does not always find the optimal solution. We rearrange the input vectors using SOM and determine the number of groups. In order to find the number of groups and grouping efficacy, we iterate K-Means algorithm changing k until we cannot obtain better solution. The results of using the proposed approach are compared to the best solutions reported in literature. The computational results show that the proposed approach provides a powerful means of solving the machine-part grouping problem. The proposed algorithm Is applied by simple calculation, so it can be for designer to change production constraints.

• 전자공학회논문지B
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• 제30B권8호
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• pp.64-70
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• 1993

This paper presents an efficient SOFM(self-organizing feature map) algorithm for the solution of the large scale TSPs(traveling salesman problems). Because no additional winner neuron for each city is created in the next competition, the proposed algorithm requires just only the N output neurons and 2N connections, which are fixed during the whole process, for N-city TSP, and it does not requires any extra algorithm of creation of deletion of the neurons. And due to direct exploitation of the output potential in adaptively controlling the neighborhood, the proposed algorithm can obtain higher convergence rate to the suboptimal solutions. Simulation results show about 30% faster convergence and better solution than the conventional algorithm for solving the 30-city TSP and even for the large scale of 1000-city TSPs.

• 대한수학회보
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• 제53권5호
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• pp.1327-1339
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• 2016

Self-organizing systems arise very naturally in artificial intelligence, and in physical, biological and social sciences. In this paper, we modify the classic Cucker-Smale model at both microscopic and macroscopic levels by taking the target motion pattern driving forces into consideration. Such target motion pattern driving force functions are properly defined for the line-shaped motion pattern and the ball-shaped motion pattern. For the modified Cucker-Smale model with the prescribed line-shaped motion pattern, we have analytically shown that there is a flocking pattern with an asymptotic flocking velocity. This is illustrated by numerical simulations using both symmetric and non-symmetric pairwise influence functions. For the modified Cucker-Smale model with the prescribed ball-shaped motion pattern, our simulations suggest that the solution also converges to the prescribed motion pattern.

• 대한전기학회논문지:전력기술부문A
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• 제51권6호
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• pp.276-283
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• 2002

This Paper Presents the method for detecting a partial discharge(PD) using an electromagnetic wave measured by an antenna. The various electromagnetic waves are measured in the laboratory and wavelet transform, which is provides a direct quantitative measure of spectral content in the time-frequency domain, are applied for identifying the property of electromagnetic waves. Also, the statistical method and self-organizing feature map(SOFM) are applied for the pattern recognition of electromagnetic waves. The proposed method is shown to be useful for detecting electromagnetic waves emitted for PD in test data.

• 정보관리학회지
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• 제18권2호
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• pp.143-164
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• 2001

본 연구는 디렉토리 검색엔진의 주제구성에 대한 문제점을 분석하고, 효율적인 데렉토리 구성과 운영을 위한 지침을 제시함으로써 인터넷 공간에서의 정보검색에 효과성을 높일 수 있도록 하였다. 연구방법으로는 연구대상인 디렉토리 검색엔진의 최상위 주제와 하위 주제를 조사하여 검색엔진들의 일반적 특성과 주제구성의 계층성, 논리성 등을 분석하였고, 이론적 배경을 위해 문헌적 연구를 병행하였다. 연구 결과로 디렉토리 구성, 주제 선정, 인터페이스, 유지·관리 등을 위한 10가지의 지침을 제시하였다.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2013년도 춘계 종합학술대회 논문집
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• pp.253-254
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• 2013

In the preceding studies, an analysis of Saga Prefectural sightseeing information by a self-organizing map (SOM) has been tried. And recent development on information and communication technology (ICT) will help us to access any results via the mobile devices easily. Then, in order to realize this basic idea, development of an application for mobile devices is investigated through some preliminary computer simulations on the standard desktop PC in this article.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.19-19
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• 2000

This paper introduces a new scheme for neural network classifier which can describe the shape of patterns in clustered group by using a self-organizing teeming algorithm. The prototype based neural network classifier can not describe the shape of group and it has low classification performance when the data groups are complex. To improve above-mentioned problem, new neural scheme is introduced. This proposed neural network algorithm can be regarded as the extension of self-organizing feature map which can describe The experimental results shows that the proposed algorithm can describe the shape of pattern successfully.

• 로봇학회논문지
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• 제3권2호
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• pp.106-111
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• 2008

This paper presents a decentralized coordination for a small-scale mobile robot teams performing a task through cooperation. Robot teams are required to generate and maintain various geometric patterns adapting to an environment and/or a task in many cooperative applications. In particular, all robots must continue to strive toward achieving the team's mission even if some members fail to perform their role. Toward this end, given the number of robots in a team, an effective coordination is investigated for decentralized formation control strategies. Specifically, all members are required first to reach agreement on their coordinate system and have an identifier (ID) for role assignment in a self-organizing way. Then, employing IDs on individual robots within a common coordinate system, a decentralized neighbor-referenced formation control is realized to generate, keep, and switch between different geometric shapes. This approach is verified using an in-house simulator and physical mobile robots. We detail and evaluate the formation control approach, whose common features include self-organization, robustness, and flexibility.